scholarly journals Barriers to Use of Clinical Decision Support for the Evaluation of Pulmonary Embolism: Results of a Qualitative Study (Preprint)

2020 ◽  
Author(s):  
Safiya Richardson
Keyword(s):  
Pulmonary Embolism ◽  
Decision Support ◽  
Qualitative Study ◽  
Clinical Decision Support ◽  
Clinical Care ◽  
Clinical Decision ◽  
Physician Assistants ◽  
Structured Interview ◽  
Barriers To Use ◽  
Behavioral Barriers

BACKGROUND Providers often disregard potentially beneficial clinical decision support (CDS). Improvements in quality of care seen with CDS have been significantly limited by consistently low provider adoption, estimated at 10%. OBJECTIVE We sought to explore the psychological and behavioral barriers to use of a CDS tool. METHODS We conducted a qualitative study involving Emergency Medicine physicians and physician assistants. A semi-structured interview guide was created based on the Capability Opportunity Motivation Behavior (COM-B) model. Interviews focused on barriers to use of a CDS tool built based on Wells’ Criteria for Pulmonary Embolism to assist providers in establishing pre-test probability of pulmonary embolism (PE) before imaging. RESULTS Interviews were conducted with 12 providers. Six barriers were identified: 1. Bayesian Reasoning, 2. Fear of Missing PE, 3. Time Pressure / Cognitive Load, 4. Gestalt Includes Wells’, 5. Missed Risk Factors, and 6. Social Pressure. CONCLUSIONS Providers highlighted several important psychological and behavioral barriers to CDS use. Addressing these barriers will be paramount in developing CDS that can meet its potential to transform clinical care. CLINICALTRIAL NA

scholarly journals Barriers to Use of Clinical Decision Support for the Evaluation of Pulmonary Embolism: Results of a Qualitative Study (Preprint)

10.2196/25046 ◽  
2020 ◽  
Author(s):  
Safiya Richardson ◽  
Katherine Dauber-Decker ◽  
Thomas McGinn ◽  
Douglas Barnaby ◽  
Adithya Cattamanchi ◽  
...  
Keyword(s):  
Pulmonary Embolism ◽  
Decision Support ◽  
Qualitative Study ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Barriers To Use

scholarly journals Barriers and facilitators to the adoption of electronic clinical decision support systems: a qualitative interview study with UK general practitioners

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Elizabeth Ford ◽  
Natalie Edelman ◽  
Laura Somers ◽  
Duncan Shrewsbury ◽  
Marcela Lopez Levy ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
General Practitioners ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Structured Interview ◽  
Qualitative Interview Study ◽  
High Level

Abstract Background Well-established electronic data capture in UK general practice means that algorithms, developed on patient data, can be used for automated clinical decision support systems (CDSSs). These can predict patient risk, help with prescribing safety, improve diagnosis and prompt clinicians to record extra data. However, there is persistent evidence of low uptake of CDSSs in the clinic. We interviewed UK General Practitioners (GPs) to understand what features of CDSSs, and the contexts of their use, facilitate or present barriers to their use. Methods We interviewed 11 practicing GPs in London and South England using a semi-structured interview schedule and discussed a hypothetical CDSS that could detect early signs of dementia. We applied thematic analysis to the anonymised interview transcripts. Results We identified three overarching themes: trust in individual CDSSs; usability of individual CDSSs; and usability of CDSSs in the broader practice context, to which nine subthemes contributed. Trust was affected by CDSS provenance, perceived threat to autonomy and clear management guidance. Usability was influenced by sensitivity to the patient context, CDSS flexibility, ease of control, and non-intrusiveness. CDSSs were more likely to be used by GPs if they did not contribute to alert proliferation and subsequent fatigue, or if GPs were provided with training in their use. Conclusions Building on these findings we make a number of recommendations for CDSS developers to consider when bringing a new CDSS into GP patient records systems. These include co-producing CDSS with GPs to improve fit within clinic workflow and wider practice systems, ensuring a high level of accuracy and a clear clinical pathway, and providing CDSS training for practice staff. These recommendations may reduce the proliferation of unhelpful alerts that can result in important decision-support being ignored.

scholarly journals XML Data and Knowledge-Encoding Structure for a Web-Based and Mobile Antenatal Clinical Decision Support System: Development Study

10.2196/17512 ◽  
2020 ◽  
Vol 4 (10) ◽  
pp. e17512
Author(s):  
Ever Augusto Torres Silva ◽  
Sebastian Uribe ◽  
Jack Smith ◽  
Ivan Felipe Luna Gomez ◽  
Jose Fernando Florez-Arango
Keyword(s):  
Decision Support ◽  
Antenatal Care ◽  
Clinical Decision Support ◽  
Web Application ◽  
Clinical Care ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Structure Design ◽  
Mobile App ◽  
Clinical Workflow

Background Displeasure with the functionality of clinical decision support systems (CDSSs) is considered the primary challenge in CDSS development. A major difficulty in CDSS design is matching the functionality to the desired and actual clinical workflow. Computer-interpretable guidelines (CIGs) are used to formalize medical knowledge in clinical practice guidelines (CPGs) in a computable language. However, existing CIG frameworks require a specific interpreter for each CIG language, hindering the ease of implementation and interoperability. Objective This paper aims to describe a different approach to the representation of clinical knowledge and data. We intended to change the clinician’s perception of a CDSS with sufficient expressivity of the representation while maintaining a small communication and software footprint for both a web application and a mobile app. This approach was originally intended to create a readable and minimal syntax for a web CDSS and future mobile app for antenatal care guidelines with improved human-computer interaction and enhanced usability by aligning the system behavior with clinical workflow. Methods We designed and implemented an architecture design for our CDSS, which uses the model-view-controller (MVC) architecture and a knowledge engine in the MVC architecture based on XML. The knowledge engine design also integrated the requirement of matching clinical care workflow that was desired in the CDSS. For this component of the design task, we used a work ontology analysis of the CPGs for antenatal care in our particular target clinical settings. Results In comparison to other common CIGs used for CDSSs, our XML approach can be used to take advantage of the flexible format of XML to facilitate the electronic sharing of structured data. More importantly, we can take advantage of its flexibility to standardize CIG structure design in a low-level specification language that is ubiquitous, universal, computationally efficient, integrable with web technologies, and human readable. Conclusions Our knowledge representation framework incorporates fundamental elements of other CIGs used in CDSSs in medicine and proved adequate to encode a number of antenatal health care CPGs and their associated clinical workflows. The framework appears general enough to be used with other CPGs in medicine. XML proved to be a language expressive enough to describe planning problems in a computable form and restrictive and expressive enough to implement in a clinical system. It can also be effective for mobile apps, where intermittent communication requires a small footprint and an autonomous app. This approach can be used to incorporate overlapping capabilities of more specialized CIGs in medicine.

scholarly journals Advances in Clinical Decision Support: Highlights of Practice and the Literature 2015-2016

2017 ◽  
Vol 26 (01) ◽  
pp. 125-132
Author(s):  
R. A. Jenders
Keyword(s):  
Clinical Practice ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Negative Impact ◽  
Clinical Care ◽  
Clinical Decision ◽  
Theory Approach ◽  
Research And Practice ◽  
Work Related ◽  
Active Research

Summary Introduction: Advances in clinical decision support (CDS) continue to evolve to support the goals of clinicians, policymakers, patients and professional organizations to improve clinical practice, patient safety, and the quality of care. Objectives: Identify key thematic areas or foci in research and practice involving clinical decision support during the 2015-2016 time period. Methods: Thematic analysis consistent with a grounded theory approach was applied in a targeted review of journal publications, the proceedings of key scientific conferences as well as activities in standards development organizations in order to identify the key themes underlying work related to CDS. Results: Ten key thematic areas were identified, including: 1) an emphasis on knowledge representation, with a focus on clinical practice guidelines; 2) various aspects of precision medicine, including the use of sensor and genomic data as well as big data; 3) efforts in quality improvement; 4) innovative uses of computer-based provider order entry (CPOE) systems, including relevant data displays; 5) expansion of CDS in various clinical settings; 6) patient-directed CDS; 7) understanding the potential negative impact of CDS; 8) obtaining structured data to drive CDS interventions; 9) the use of diagnostic decision support; and 10) the development and use of standards for CDS. Conclusions: Active research and practice in 2015-2016 continue to underscore the importance and broad utility of CDS for effecting change and improving the quality and outcome of clinical care.

scholarly journals Interviews with experts in rare diseases for the development of clinical decision support system software - a qualitative study

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Jannik Schaaf ◽  
Hans-Ulrich Prokosch ◽  
Martin Boeker ◽  
Johanna Schaefer ◽  
Jessica Vasseur ◽  
...  
Keyword(s):  
Decision Support ◽  
Qualitative Study ◽  
Medical Informatics ◽  
Clinical Decision Support ◽  
Rare Diseases ◽  
Qualitative Content Analysis ◽  
Medical Center ◽  
Clinical Decision ◽  
Diagnostic Process ◽  
University Hospitals

Abstract Background Patients with rare diseases (RDs) are often diagnosed too late or not at all. Clinical decision support systems (CDSSs) could support the diagnosis in RDs. The MIRACUM (Medical Informatics in Research and Medicine) consortium, which is one of four funded consortia in the German Medical Informatics Initiative, will develop a CDSS for RDs based on distributed clinical data from ten university hospitals. This qualitative study aims to investigate (1) the relevant organizational conditions for the operation of a CDSS for RDs when diagnose patients (e.g. the diagnosis workflow), (2) which data is necessary for decision support, and (3) the appropriate user group for such a CDSS. Methods Interviews were carried out with RDs experts. Participants were recruited from staff physicians at the Rare Disease Centers (RDCs) at the MIRACUM locations, which offer diagnosis and treatment of RDs. An interview guide was developed with a category-guided deductive approach. The interviews were recorded on an audio device and then transcribed into written form. We continued data collection until all interviews were completed. Afterwards, data analysis was performed using Mayring’s qualitative content analysis approach. Results A total of seven experts were included in the study. The results show that medical center guides and physicians from RDC B-centers (with a focus on different RDs) are involved in the diagnostic process. Furthermore, interdisciplinary case discussions between physicians are conducted. The experts explained that RDs exist which cannot be fully differentiated, but rather described only by their overall symptoms or findings: diagnosis is dependent on the disease or disease group. At the end of the diagnostic process, most centers prepare a summary of the patient case. Furthermore, the experts considered both physicians and experts from the B-centers to be potential users of a CDSS. The experts also have different experiences with CDSS for RDs. Conclusions This qualitative study is a first step towards establishing the requirements for the development of a CDSS for RDs. Further research is necessary to create solutions by also including the experts on RDs.

scholarly journals Informatics and interaction: Applying human factors principles to optimize the design of clinical decision support for sepsis

2019 ◽  
Vol 26 (1) ◽  
pp. 642-651
Author(s):  
Laura Schubel ◽  
Danielle L Mosby ◽  
Joseph Blumenthal ◽  
Muge Capan ◽  
Ryan Arnold ◽  
...  
Keyword(s):  
Information Technology ◽  
Decision Support ◽  
Human Factors ◽  
Organ Failure ◽  
Health Information Technology ◽  
Health Information ◽  
Clinical Decision Support ◽  
Clinical Care ◽  
Clinical Decision ◽  
Wide Range

In caring for patients with sepsis, the current structure of electronic health record systems allows clinical providers access to raw patient data without imputation of its significance. There are a wide range of sepsis alerts in clinical care that act as clinical decision support tools to assist in early recognition of sepsis; however, there are serious shortcomings in existing health information technology for alerting providers in a meaningful way. Little work has been done to evaluate and assess existing alerts using implementation and process outcomes associated with health information technology displays, specifically evaluating clinician preference and performance. We developed graphical model displays of two popular sepsis scoring systems, quick Sepsis Related Organ Failure Assessment and Predisposition, Infection, Response, Organ Failure, using human factors principles grounded in user-centered and interaction design. Models will be evaluated in a larger research effort to optimize alert design to improve the collective awareness of high-risk populations and develop a relevant point-of-care clinical decision support system for sepsis.

Human-centred design processes for clinical decision support: A pulmonary embolism case study

2020 ◽  
Vol 142 ◽  
pp. 104196
Author(s):  
Julie N. Babione ◽  
Wrechelle Ocampo ◽  
Sydney Haubrich ◽  
Connie Yang ◽  
Torre Zuk ◽  
...  
Keyword(s):  
Pulmonary Embolism ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Design Processes ◽  
Human Centred Design
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